The Advanced Television Systems Committee (ATSC) standard for Digital Television (DTV) in the United States requires an 8-VSB transmission system which includes Forward Error Correction (FEC) as a means of improving system performance. (United States Advanced Television Systems Committee, “ATSC Digital Television Standard”, (document A53.doc), Sep. 16, 1995.) FIG. 1 shows a simplified block diagram of a typical ATSC compliant DTV transmitter and receiver, emphasizing the FEC subsystem. As shown in FIG. 1, on the transmitter side, the FEC encoding subsystem includes a Reed-Solomon (RS) encoder, followed by a byte interleaver, and a trellis encoder. The FEC encoding subsystem is preceded by a data randomizer and followed by an 8-VSB modulator. On the receiver side, there is a corresponding FEC decoding subsystem which includes a trellis decoder, a byte de-interleaver and a RS decoder. The FEC decoding subsystem is preceded by an 8-VSB demodulator and followed by a data de-randomizer.
The ATSC DTV transmission scheme is not robust enough against Doppler shift and multipath radio interference, and is designed for highly directional fixed antennas, hindering the provision of expanded services to customers using mobile and handheld (M/H) devices. In an attempt to address these issues and to create a more robust and flexible system, it has been proposed, among other things, to add a new layer of FEC coding and more powerful decoding algorithms to decrease the Threshold of Visibility (TOV). (See, e.g., International Patent Publication No. WO 2008/144004 A1.) The added layer of FEC coding may require decoding techniques such as iterative (turbo) decoding (see, e.g., C. Berrou et al., “Near Shannon Limit Error—Correcting Coding and Decoding: Turbo-Codes (1)”, Proceedings of the IEEE International Conference on Communications—ICC'93, May 23-26, 1993, Geneva, Switzerland, pp. 1064-1070; and M. R. Soleymani et al., “Turbo Coding for Satellite and Wireless Communications”, Kluwer Academic Publishers, USA, 2002) and trellis decoding algorithms like the MAP decoder (see, e.g., L. R. Bahl et al., “Optimal Decoding of Linear Codes for Minimizing Symbol Error Rate”, IEEE Transactions on Information Theory, Vol. IT-20, No. 2, March 1974, pp. 284-287.)